Machine Learning Challenges : Evaluating Predictive Uncertainty, Visual Object Classification, and Recognizing Textual Entailment, First Pascal Machine Learning Challenges Workshop, MLCW 2005, Southampton, UK, April 11-13, 2005, Revised Selected Papers / edited by Joaquin Quinonero-Candela, Ido Dagan, Bernardo Magnini, Florence d'Alché-Buc.

Format:

Book

Contributor:

Quiñonero-Candela, Joaquin, editor.

Dagan, Ido, editor.

Magnini, Bernardo, editor.

d'Alché-Buc, Florence, editor.

SpringerLink (Online service)

Series:

Computer Science (Springer-11645)

Lecture notes in computer science. Lecture notes in artificial intelligence ; 3944.

Lecture Notes in Artificial Intelligence ; 3944

Language:

English

Subjects (All):

Artificial intelligence.

Algorithms.

Logic, Symbolic and mathematical.

Natural language processing (Computer science).

Optical data processing.

Pattern perception.

Artificial Intelligence.

Algorithm Analysis and Problem Complexity.

Mathematical Logic and Formal Languages.

Natural Language Processing (NLP).

Image Processing and Computer Vision.

Pattern Recognition.

Local Subjects:

Artificial Intelligence.

Algorithm Analysis and Problem Complexity.

Mathematical Logic and Formal Languages.

Natural Language Processing (NLP).

Image Processing and Computer Vision.

Pattern Recognition.

Physical Description:

1 online resource (XIII, 462 pages).

Edition:

First edition 2006.

Contained In:

Springer eBooks

Place of Publication:

Berlin, Heidelberg : Springer Berlin Heidelberg : Imprint: Springer, 2006.

System Details:

text file PDF

Contents:

Evaluating Predictive Uncertainty Challenge

Classification with Bayesian Neural Networks

A Pragmatic Bayesian Approach to Predictive Uncertainty

Many Are Better Than One: Improving Probabilistic Estimates from Decision Trees

Estimating Predictive Variances with Kernel Ridge Regression

Competitive Associative Nets and Cross-Validation for Estimating Predictive Uncertainty on Regression Problems

Lessons Learned in the Challenge: Making Predictions and Scoring Them

The 2005 PASCAL Visual Object Classes Challenge

The PASCAL Recognising Textual Entailment Challenge

Using Bleu-like Algorithms for the Automatic Recognition of Entailment

What Syntax Can Contribute in the Entailment Task

Combining Lexical Resources with Tree Edit Distance for Recognizing Textual Entailment

Textual Entailment Recognition Based on Dependency Analysis and WordNet

Learning Textual Entailment on a Distance Feature Space

An Inference Model for Semantic Entailment in Natural Language

A Lexical Alignment Model for Probabilistic Textual Entailment

Textual Entailment Recognition Using Inversion Transduction Grammars

Evaluating Semantic Evaluations: How RTE Measures Up

Partial Predicate Argument Structure Matching for Entailment Determination

VENSES - A Linguistically-Based System for Semantic Evaluation

Textual Entailment Recognition Using a Linguistically-Motivated Decision Tree Classifier

Recognizing Textual Entailment Via Atomic Propositions

Recognising Textual Entailment with Robust Logical Inference

Applying COGEX to Recognize Textual Entailment

Recognizing Textual Entailment: Is Word Similarity Enough?.

Other Format:

Printed edition:

ISBN:

978-3-540-33428-6

9783540334286

Access Restriction:

Restricted for use by site license.